Factors Influencing the Acceptance of Robo-Taxi Services in China: An Extended Technology Acceptance Model Analysis

Author:

Liu Mingyu1ORCID,Wu Jianping1ORCID,Zhu Chunli2ORCID,Hu Kezhen3ORCID

Affiliation:

1. Department of Civil Engineering, Tsinghua University, Beijing 100084, China

2. School of Information and Electronics & Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing 100081, China

3. China Academy of Information and Communication Technology, Beijing 100191, China

Abstract

With the development of autonomous driving technologies, robo-taxis (shared autonomous vehicles) are being tested on real roads. In China, in particular, people in some cities such as Beijing and Shanghai can book a robo-taxi online and experience the service. To examine the influential factors on user acceptance of robo-taxi services, this study proposes and employs an extended technology acceptance model (TAM) with four external factors: perceived trust, government support, social influence, and perceived enjoyment. Data were collected through an online questionnaire in China, and responses from 403 respondents were analyzed using structural equation modeling. Both typical TAM factors—including perceived ease of use, perceived usefulness, and attitude—and external factors were found to play significant roles in predicting users’ intention to use robo-taxis. The four external factors influenced the user acceptance indirectly via typical TAM factors. Improving users’ perceived trust is important for increasing public adoption. A greater emphasis by manufacturers on safety concerns, wider dissemination of information on data protection and safety systems, and government support through incentives for manufacturers and users can help improve public adoption of robo-taxi services.

Funder

NSFC Zhejiang Joint Fund for the Integration of Industrialization and Informatization

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

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